In recent years researchers have become increasingly interested in the multi-label and hierarchical learning approaches, finding many application to several domain, including classification [1]}, [2]}, image annotation [3]}, bioinformatics [4]}, [5]} [6]} [7]}.
Nowadays, machine learning is commonly used to resolve complex problem into pattern recognition where an object is classified assigning a label in according with the model's rule used.
However, classes are not always disjoint from others and objects within them can be related to others as a hierarchical structure [8]}.
Human beings perceive the world with different types of granularity and can translate information from coarse-grained to fine-grained and on the contrary, perceiving different levels of abstraction of the information acquired [9]}, [10]}.
This concept is reflected in the taxonomy of the multi-label general approaches under the idea of structured output prediction [11]}.
